PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdtn: <http://www.wikidata.org/prop/direct-normalized/>
SELECT ?mount ?mountLabel ?elevation ?astrBody WHERE {
  ?mount wdt:P31 / wdt:P279 * wd:Q8502 ; wdtn:P2044 ?elevation .
  OPTIONAL {
    ?mount wdt:P376 ?astrBody
  }
  FILTER ( ?elevation > 8000 ) FILTER ( ! BOUND( ?astrBody ) || ?astrBody = wd:Q2 ) OPTIONAL {
    ?mount rdfs:label ?mountLabel FILTER ( LANG( ?mountLabel ) = "en" )
  }
}
ORDER BY DESC ( ?elevation )

Do you mean (A) exclude all mountains that have any "located on astronomical body" statement (which would also exclude Earth), or (B) exclude mountains on astronomical bodies other than Earth (i.e., exclude extraterrestrial mountains like Olympus Mons)? Which interpretation should I use?

What are the mountains with an elevation above sea level greater than 8000 meters, excluding those located on any astronomical body?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the mountains with an elevation above sea level greater than 8000 meters, excluding those located on any astronomical body?

[Assistant] I will search Wikidata for relevant entities and properties: the class for mountain, the elevation above sea level property, and the property that indicates the astronomical body a feature is located on (so I can exclude non-Earth mountains). I'll run entity and property searches to confirm identifiers. I will explain each step and show intermediate findings.

[Tool]
Top 10 entity alternatives:
1. mountain, also known as mt., mtn., mountains, mount (wd:Q8502)
2. Mountain (wd:Q1255792): instance of musical group, American band
3. Mountain, also known as Mountain, North Dakota, Mountain, ND (wd:Q2032181): instance of city in the United States, city in North Dakota, USA
4. Mountain, also known as Town of Mountain (wd:Q1885759): civil town in Oconto County, Wisconsin, instance of civil town of Wisconsin
5. The Mountain, also known as Mountain (wd:Q910112): 1956 film by Edward Dmytryk, instance of film
6. The Mountain, also known as Mountain (wd:Q1192451): 1991 film by Markus Imhoof, instance of film
7. 4-8-2, also known as 2D1, Mountain, Mohawk, 4/7, 241 (wd:Q1473477)
8. Mountain (wd:Q13422857): instance of census-designated place in the United States, human settlement in Wisconsin, United States of America
9. Mountain (wd:Q29293936): 2014 simulation video game, instance of video game
10. The Mountain, also known as Dag 2, Mountain (wd:Q7752476): 2012 Turkish film by Alper Çağlar, instance of film

[Tool]
Top 10 property alternatives:
1. located on astronomical body, also known as on astronomical body, on astronomical location (wd:P376 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): single astronomical body on which features or places are situated
2. parent astronomical body, also known as orbits, parent body, planetary system, primary, star (wd:P397 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): major astronomical body the item belongs to
3. companion of, also known as has companion, has astronomical companion, companion, astronomic companion of, astronomical companion of (wd:P399 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): two or more astronomic bodies of the same type relating to each other
4. site of astronomical discovery, also known as observatory site of discovery, observatory of discovery, discovered at observatory, astronomical discovery site (wd:P65 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): the place where an astronomical object was discovered (observatory, satellite), subproperty of location of discovery
5. constellation, also known as part of constellation (wd:P59 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): the area of the celestial sphere of which the subject is a part (from a scientific standpoint, not an astrological one), subproperty of part of
6. child astronomical body, also known as child body, has moon, has planet, orbited by, satellite (wd:P398 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): minor body that belongs to the item
7. located in/on physical feature, also known as on geographical feature, on, loc (terr), located on the terrain feature, location (terrain feature) (wd:P706 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., subproperty of location, subproperty of part of
8. astronomic symbol image, also known as planetary symbol image, planetary symbol, astronomic symbol, astronomical symbol image, astronomical symbol (wd:P367 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): image of the symbol that identify a planet or an asteroid of the solar system, subproperty of icon
9. catalog code, also known as identifier in catalog, registration number, register, enrollment number, cat. no. (wd:P528 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): catalog name of an object, use with qualifier P972
10. location of discovery, also known as found in, location of discovered object, findspot, place of discovery, site of discovery (wd:P189 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): where the item was located when discovered, subproperty of significant place

[Assistant] I'll search for the property used for elevation above sea level in Wikidata. Then I'll look for the mountain class and confirm relevant properties. I'll run property searches now.

[Tool]
Top 10 property alternatives:
1. elevation above sea level, also known as elevation, MASL, MAMSL, height, elevation above mean sea level (wd:P2044 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): height of the item (geographical object) as measured relative to sea level
2. clearance, also known as span height, air draught, height of deck bottom, height above water, height above valley floor (wd:P2793 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): distance between surface under bridge and bottom of a bridge deck
3. highest point, also known as zenith, tallest point, summit, pinnacle, highest peak (wd:P610 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): point with highest elevation in a region or path, subproperty of has part(s)
4. floors above ground, also known as floor count, levels above ground, number of floors, number of stories, storeys (wd:P1101 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): above ground floor count of a building (ground floor and attic included)
5. located in or next to body of water, also known as on lake, next to lake, on harbour, located in water, on coast of (wd:P206 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): body of water on or next to which a place is located, subproperty of location
6. property, also known as allowed qualifier (wd:P2306 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): qualifier to define a property constraint in combination with P2...traint), or to limit the scope of Q44292881 (wikidata statement)
7. Wikidata property, also known as has property, main property, property, property for this item (wd:P1687 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): main Wikidata property for this item
8. item of property constraint, also known as item qualifier, value, qid, property value, item of constraint (wd:P2305 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): qualifier to define a property constraint in combination with "property constraint" (P2302)
9. located in/on physical feature, also known as on geographical feature, on, loc (terr), located on the terrain feature, location (terrain feature) (wd:P706 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., subproperty of location, subproperty of part of
10. country, also known as state, sovereign state, land, host country (wd:P17 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): sovereign state that this item is in (not to be used for human beings), subproperty of located in the administrative territorial entity

[Assistant] I'll run a SPARQL query to find items with an elevation above sea level (wdt:P2044) greater than 8000 to get candidate mountains. I'll start without restricting to the mountain class to see what's in the data.

[Tool]
Got 100 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                                         | itemLabel                          | elevation           |
| -------------------------------------------- | ---------------------------------- | ------------------- |
| noctilucent cloud (wd:Q192794)               | noctilucent cloud (en)             | 76000 (xsd:decimal) |
| cirrus uncinus (wd:Q1124042)                 | cirrus uncinus (en)                | 23000 (xsd:decimal) |
| Rheasilvia central peak (wd:Q21838035)       | Rheasilvia central peak (en)       | 22000 (xsd:decimal) |
| Bosler Junction (wd:Q30622133)               | Bosler Junction (en)               | 21474 (xsd:decimal) |
| Olympus Mons (wd:Q520)                       | Olympus Mons (en)                  | 21229 (xsd:decimal) |
| ...                                          | ...                                | ...                 |
| Casco Peak (wd:Q14684358)                    | Casco Peak (en)                    | 13915 (xsd:decimal) |
| Red Mountain (wd:Q14685073)                  | Red Mountain (en)                  | 13914 (xsd:decimal) |
| Emerald Peak (wd:Q14684482)                  | Emerald Peak (en)                  | 13911 (xsd:decimal) |
| Horseshoe Mountain (Colorado) (wd:Q14684599) | Horseshoe Mountain (Colorado) (en) | 13905 (xsd:decimal) |
| Mount Agassiz (wd:Q6919275)                  | Mount Agassiz (en)                 | 13899 (xsd:decimal) |

[Assistant] Now I'll query for items that are instances of mountain (wd:Q8502) with elevation above 8000 (wdt:P2044), and I'll exclude items that have a located on astronomical body (wdt:P376) different from Earth (wd:Q2). I'll allow items without P376 specified (most Earth mountains may not have that statement). I'll execute the query to see results.

[Tool]
Got 1,160 rows and 4 columns, showing the first 5 and last 5 rows below:
| mount                          | mountLabel            | elevation           | astrBody |
| ------------------------------ | --------------------- | ------------------- | -------- |
| Peak 17400 (wd:Q123374100)     | Peak 17400 (en)       | 17450 (xsd:decimal) |          |
| Mount Blackburn (wd:Q1520855)  | Mount Blackburn (en)  | 16390 (xsd:decimal) |          |
| Mount Belford (wd:Q6919666)    | Mount Belford (en)    | 14203 (xsd:decimal) |          |
| Crestone Needle (wd:Q945543)   | Crestone Needle (en)  | 14203 (xsd:decimal) |          |
| Mount Bross (wd:Q6919868)      | Mount Bross (en)      | 14178 (xsd:decimal) |          |
| ...                            | ...                   | ...                 | ...      |
| Warner Peak (wd:Q48780363)     | Warner Peak (en)      | 8012 (xsd:decimal)  |          |
| Double Crater (wd:Q5299682)    | Double Crater (en)    | 8007 (xsd:decimal)  |          |
| Bashful Peak (wd:Q4866805)     | Bashful Peak (en)     | 8005 (xsd:decimal)  |          |
| McMillan Spire (wd:Q14713812)  | McMillan Spire (en)   | 8004 (xsd:decimal)  |          |
| Terrace Mountain (wd:Q7703183) | Terrace Mountain (en) | 8002 (xsd:decimal)  |          |

[Assistant] I'll run a refined query using the normalized elevation property wdtn:P2044 (meters) and restrict to items that are instance of mountain (Q8502). I'll exclude items that have a located on astronomical body (P376) that is not Earth (Q2). I'll retrieve labels and elevation in meters.

[Tool] Got no rows and 4 columns

[Assistant] Do you mean (A) exclude all mountains that have any "located on astronomical body" statement (which would also exclude Earth), or (B) exclude mountains on astronomical bodies other than Earth (i.e., exclude extraterrestrial mountains like Olympus Mons)? Which interpretation should I use?


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?event ?eventLabel ?tournament ?tournamentLabel WHERE {
  ?event wdt:P31 wd:Q46190676 ; wdt:P2094 wd:Q16893072 ; wdt:P361 ?tournament .
  FILTER NOT EXISTS {
    ?event wdt:P1346 ?winner .
  }
  ?tournament wdt:P361 * ?series .
  FILTER ( ?series = wd:Q300008 || ?series = wd:Q3775082 ) OPTIONAL {
    ?event rdfs:label ?eventLabel FILTER ( lang( ?eventLabel ) = "en" )
  }
  OPTIONAL {
    ?tournament rdfs:label ?tournamentLabel FILTER ( lang( ?tournamentLabel ) = "en" )
  }
}
ORDER BY ?eventLabel

I executed the query and it returned 24 men's singles tennis event items (their IRIs are returned as ?event) that have no winner (no wdt:P1346) and whose tournament (via wdt:P361) is part, possibly recursively, of either the ATP Tour (wd:Q300008) or the Grand Prix tennis circuit (wd:Q3775082). The query also returns English labels for the events and tournaments when available. Example returned rows include:
- wd:Q3674888  "1996 Salem Open Beijing – singles"  part of wd:Q3674884 "1996 Salem Open Beijing and the Nokia Open"
- wd:Q3994371  "2003 Open SEAT Godó – singles"  part of wd:Q3994368 "2003 Open SEAT Godó"
- wd:Q3883469  "2005 Open d'Orléans – singles"  part of wd:Q3883467 "2005 Open d'Orléans"
- wd:Q134481286 "2025 Geneva Open – Singles" part of wd:Q134127232 "2025 Geneva Open"
- wd:Q132173811 "2025 Open 13 Provence – Singles" part of wd:Q131860197 "2025 Open 13 Provence"

If you want, I can return the full list of all 24 event IRIs and their tournament IRIs/labels, or format the results as a CSV.

What are the men's singles tennis events that do not have a winner indicated and are part of a tournament that belongs to either the ATP Tour or the Grand Prix tennis circuit?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the men's singles tennis events that do not have a winner indicated and are part of a tournament that belongs to either the ATP Tour or the Grand Prix tennis circuit?

[Assistant] Step 1 — I'll search for items and properties for "men's singles", "winner", and properties linking events to tournaments and tournaments to circuits (ATP Tour, Grand Prix tennis circuit). I'll start by finding the item for "men's singles" and for the circuits. I'll also look for the property used for "winner" and for linking an event to the tournament it is part of. I'll use the search tools and explain results.

[Tool]
Top 10 entity alternatives:
1. men's singles, also known as men single skating (wd:Q4305887)
2. men's singles, also known as men's singles in tennis (wd:Q16893072): instance of sports discipline, instance of competition class, instance of men's singles, discipline in tennis
3. men's singles (wd:Q55581668): three-cushion billiards competition class, instance of competition class
4. men's singles, also known as men's individual (wd:Q61588168)
5. men's singles, also known as men's singles in badminton (wd:Q28105722): sports discipline in badminton, instance of competition class, instance of sports discipline, instance of men's singles
6. single luge, also known as men's singles, women's singles, singles (luge), single luger (wd:Q28913513)
7. wheelchair tennis men's singles, also known as wheelchair men's singles (wd:Q50211922): competition class in wheelchair tennis, instance of competition class, instance of sports discipline, instance of men's singles
8. senior men's singles, also known as champions men's singles, legends men's singles (wd:Q50825939): instance of competition class, tennis discipline
9. senior men's singles (wd:Q116481567): competition class of figure skating, instance of competition class
10. 2022 French Open – men's singles, also known as 2022 Roland-Garros – Men's singles (wd:Q107126329): instance of tennis event, tennis championship

[Tool]
Top 10 property alternatives:
1. point in time, also known as year, when, time of event, time, during (wd:P585 as wdt/p): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
2. competition class, also known as disability sport classifications, weight class, rated at, qualifies for, qualification class (wd:P2094 as wdt/p): official classification by a regulating body under which the sub...ents, teams, participants, or equipment) qualifies for inclusion
3. edition number, also known as number of event, software version number, version number (wd:P393 as wdt/p): number of an edition (first, second, ... as 1, 2, ...) or event, subproperty of series ordinal
4. country, also known as state, sovereign state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), subproperty of located in the administrative territorial entity
5. number of participants, also known as qty participants, number of competitors, participants, participant count, number of teams (wd:P1132 as wdt/p): number of participants of an event, e.g. people or groups of people that take part in the event (NO units), subproperty of quantity
6. part of, also known as meronym of, contained within, of, part of-property, section of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
7. location, also known as neighborhood, locale, neighbourhood, place, place held (wd:P276 as wdt/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
8. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
9. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt/p): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, subproperty of participating team, subproperty of participant
10. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as wdt/p): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform

No other items found

[Assistant] Next I'll search for the entities "ATP Tour" and "Grand Prix tennis circuit", and look for the property used to indicate which tournament an event is part of. I'll run searches for those entities and for a "tournament" property.

[Tool]
Top 10 entity alternatives:
1. ATP Tour, also known as ATP World Tour (wd:Q300008)
2. ATP World Tour 250 series, also known as ATP 250 Series, International Series Tournaments, International Series tennis tournaments, International Series events, ATP World Tour 250 (wd:Q300017)
3. ATP Tour Awards (wd:Q434468): ATP tennis awards for men, instance of tennis award
4. ATP Challenger Tour, also known as Challenger tennis tournament, Challenger event, Challenger tennis events, Challenger tennis event, Challenger tennis (wd:Q299345)
5. 2011 ATP World Tour, also known as 2011 atp tour (wd:Q300013): instance of tennis tour edition, men's tennis circuit
6. 2010 ATP World Tour, also known as 2010 atp tour (wd:Q300012): instance of tennis tour edition, tennis circuit
7. 2023 ATP Tour (wd:Q111441127): instance of tennis tour edition, men's tennis circuit
8. 2009 ATP World Tour, also known as Juego 2000 Calendar, Tennis 2009 Calendare ATP ITF, ATP Tour 2009, 2009 ATP Tour, 2009 atp tour (wd:Q300011): instance of tennis tour edition, tennis circuit
9. 2022 ATP Tour (wd:Q109743038): instance of tennis tour edition, men's tennis circuit
10. 2020 ATP Tour (wd:Q62083037): instance of tennis tour edition, men's tennis circuit

[Tool]
Top 10 entity alternatives:
1. Grand Prix tennis circuit (wd:Q3775082)
2. Grand Prix Circuit (wd:Q2444507): instance of video game, 1988 video game
3. Grand Prix Tennis (wd:Q30896069): instance of video game
4. Albert Park Circuit, also known as Australian Grand Prix Circuit, Melbourne Grand Prix Circuit (wd:Q171288): street circuit in Melbourne, Victoria, Australia, instance of street circuit
5. Kyalami, also known as Kyalami Grand Prix Circuit (wd:Q171667): instance of motorsport racing track, Race track in South Africa
6. Porsche Tennis Grand Prix (wd:Q311783)
7. Dallas Grand Prix Circuit (wd:Q16040264): Formula One circuit in Dallas, Texas, instance of motorsport racing track
8. Madrid Tennis Grand Prix (wd:Q299532)
9. 1970 Grand Prix circuit (wd:Q3465182): instance of tennis tour edition, tennis circuit
10. 1989 Grand Prix circuit (wd:Q3465367): instance of tennis tour edition, tennis circuit edition

[Assistant] I'll inspect a known men's singles event item (2022 French Open – men's singles) to see how events link to tournaments and how winners are represented. I'll list triples for that subject.

[Tool]
Got 94 rows and 3 columns, showing the first 10 rows below:
| subject                                          | property                           | object                                           |
| ------------------------------------------------ | ---------------------------------- | ------------------------------------------------ |
| 2022 French Open – men's singles (wd:Q107126329) | instance of (wdt:P31)              | tennis event (wd:Q46190676)                      |
| 2022 French Open – men's singles (wd:Q107126329) | country (wdt:P17)                  | France (wd:Q142)                                 |
| 2022 French Open – men's singles (wd:Q107126329) | part of (wdt:P361)                 | 2022 French Open (wd:Q107026465)                 |
| 2022 French Open – men's singles (wd:Q107126329) | location (wdt:P276)                | Stade Roland Garros (wd:Q1613027)                |
| 2022 French Open – men's singles (wd:Q107126329) | sport (wdt:P641)                   | tennis (wd:Q847)                                 |
| 2022 French Open – men's singles (wd:Q107126329) | follows (wdt:P155)                 | 2021 French Open – men's singles (wd:Q99526058)  |
| 2022 French Open – men's singles (wd:Q107126329) | followed by (wdt:P156)             | 2023 French Open – Men's singles (wd:Q112433332) |
| 2022 French Open – men's singles (wd:Q107126329) | point in time (wdt:P585)           | 2022-01-01T00:00:00Z (xsd:dateTime)              |
| 2022 French Open – men's singles (wd:Q107126329) | number of participants (wdt:P1132) | 128 (xsd:decimal)                                |
| 2022 French Open – men's singles (wd:Q107126329) | winner (wdt:P1346)                 | Rafael Nadal (wd:Q10132)                         |
| ...                                              | ...                                | ...                                              |

[Assistant] I'll inspect a tournament item (2022 French Open) to see how tournaments indicate membership in a tour/circuit. I'll list triples for that tournament.

[Tool]
Got 176 rows and 3 columns, showing the first 10 rows below:
| subject                          | property                                                    | object                                                                                |
| -------------------------------- | ----------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| 2022 French Open (wd:Q107026465) | instance of (wdt:P31)                                       | French Open (wd:Q43605)                                                                                |
| 2022 French Open (wd:Q107026465) | country (wdt:P17)                                           | France (wd:Q142)                                                                                |
| 2022 French Open (wd:Q107026465) | located in the administrative territorial entity (wdt:P131) | Paris (wd:Q90)                                                                                |
| 2022 French Open (wd:Q107026465) | Commons category (wdt:P373)                                 | 2022 Roland Garros                                                                                |
| 2022 French Open (wd:Q107026465) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Kecmanovic%20RG22%20%2816%29%20%2852144307779%29.jpg> |
| 2022 French Open (wd:Q107026465) | location (wdt:P276)                                         | Stade Roland Garros (wd:Q1613027)                                                                         |
| 2022 French Open (wd:Q107026465) | has part(s) (wdt:P527)                                      | 2022 French Open – men's singles (wd:Q107126329)                                                          |
| 2022 French Open (wd:Q107026465) | sport (wdt:P641)                                            | tennis (wd:Q847)                                                                                |
| 2022 French Open (wd:Q107026465) | official website (wdt:P856)                                 | <https://www.rolandgarros.com/en-us/>                                                                     |
| 2022 French Open (wd:Q107026465) | follows (wdt:P155)                                          | 2021 French Open (wd:Q99526045)                                                                           |
| ...                              | ...                                                         | ...                                                                                |

[Assistant] I need to find tournaments that "belong to either the ATP Tour or the Grand Prix tennis circuit". Let's inspect how tournaments indicate belonging to a tour/circuit. Search for property like "tour" or "circuit" or "part of the tour". I'll search for properties related to "tour" or "tennis circuit".

[Tool]
Top 10 property alternatives:
1. ATP tennis tournament ID (wd:P3456 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): tournament made for atp tennis players
2. ATP player ID, also known as ATP ID, ATP identifier, ATP player identifier (wd:P536 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): ATP tennis male player identifier
3. Tennis Abstract player ID, also known as tennisabstract.com player ID, tennisabstract.com player identifier, Tennis Abstract player identifier (wd:P10028 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): identifier for a player at tennisabstract.com
4. ITF player ID 2020, also known as International Tennis Federation player identifier 2020, ITF player identifier 2020, International Tennis Federation player ID 2020 (wd:P8618 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): identifier for a tennis player at the International Tennis Federation (ITF) website as of 2020
5. ITF tournament ID (wd:P6841 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): identifier for a tennis tournament edition in the International Tennis Federation database
6. Tennis Archives player ID, also known as tennisarchives.com player ID, tennisarchives.com player identifier, Tennis Archives player identifier (wd:P3670 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): ID of a tennis player at the Tennis Archives
7. Wimbledon player ID (wd:P4503 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): identifier for a tennis player on the Wimbledon website, in the archive section
8. Tennis Temple player ID, also known as tennistemple.com player ID, tennistemple.com player identifier, Tennis Temple player identifier (wd:P4544 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): identifier for a player on the Tennis Temple website
9. WTA tennis tournament ID (wd:P3469 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): identifier for tennis tournaments in the database of the Women’s Tennis Association
10. won sets (wd:P11081 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): number of sets won

[Assistant] Not seeing a direct property. But tournaments might have "tour" or "part of" linking to a "ATP Tour" or "Grand Prix tennis circuit". Let's search tournaments that have "part of" relationships to ATP Tour or Grand Prix. I will search for tournaments that have a property pointing to wd:Q300008 or wd:Q3775082.

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                                                | property           | object                |
| ------------------------------------------------------ | ------------------ | --------------------- |
| ATP Finals (wd:Q270907)                                | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| ATP Tour Masters 1000 (wd:Q300029)                     | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| ATP World Tour 250 series (wd:Q300017)                 | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| ATP World Tour 500 series (wd:Q300018)                 | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| Laver Cup (wd:Q26694763)                               | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| Washington Open (wd:Q299950)                           | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| ATP Challenger Tour (wd:Q299345)                       | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| Gijón Open (wd:Q113950895)                             | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| Hangzhou Open (wd:Q130237551)                          | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| 2011 U.S. Men's Clay Court Championships (wd:Q1575064) | part of (wdt:P361) | ATP Tour (wd:Q300008) |
| ...                                                    | ...                | ...                   |

[Assistant]
That shows tournaments or series that are part of ATP Tour. But user asked: "men's singles tennis events that do not have a winner indicated and are part of a tournament that belongs to either the ATP Tour or the Grand Prix tennis circuit." So we need to find tennis event items (instance of tennis event) with sport tennis, that are men's singles (maybe have "men's singles" in their label or have "competition class" property?), and have no wdt:P1346 (winner) statement, and are part of a tournament (wdt:P361 or part of another series?) whose item has P361 to ATP Tour or Grand Prix circuit.

Plan:
- Find items ?event with wdt:P31 wd:Q46190676 (tennis event). Filter that it's men's singles: maybe has "sport" tennis and has "competition class" indicates men's singles? Alternatively many event items are named "... – men's singles" and have 'part of' pointing to tournament edition. In example above, 2022 French Open – men's singles has instance of tennis event. It also has 'part of' linking to tournament edition. We can require that the event's label contains "men's singles" string? But per rule, avoid relying on labels; better to require competition class property? Search for property for competition class earlier: P2094 "competition class". Let's search events with P2094 value representing men's singles class (wd:Q16893072?). We found an entity Q16893072 earlier as "men's singles in tennis". Let's inspect it.

[Tool]
Top 10 entity alternatives:
1. men's singles, also known as men's singles in tennis (wd:Q16893072): instance of sports discipline, instance of competition class, instance of men's singles, discipline in tennis
2. wheelchair tennis men's singles, also known as wheelchair men's singles (wd:Q50211922): competition class in wheelchair tennis, instance of competition class, instance of sports discipline, instance of men's singles
3. all-time tennis records – men's singles, also known as all-time tennis records - men's singles, overall tennis records - men's singles, overall tennis records – men's singles (wd:Q17016846)
4. 2011 Dubai Tennis Championships – men's singles (wd:Q1822061): 2011 tennis event results, instance of tennis event
5. 2013 Sony Open Tennis – men's singles (wd:Q7724928): 2013 tennis event results, instance of tennis event
6. 2023 Dubai Tennis Championships – Men's singles (wd:Q116897745): 2023 tennis event results, instance of tennis event
7. 2022 Dubai Tennis Championships – men's singles (wd:Q110953898): 2022 tennis event results, instance of tennis event
8. 2009 Dubai Tennis Championships – men's singles (wd:Q15262709): 2009 tennis event results, instance of tennis event
9. 2020 Dubai Tennis Championships – men's singles (wd:Q85982068): 2020 tennis event results, instance of tennis event
10. 2019 Dubai Tennis Championships – men's singles (wd:Q61856750): instance of tennis event, tennis tournament event

[Tool]
Got 1 row and 3 columns:
| subject                                          | property                      | object                       |
| ------------------------------------------------ | ----------------------------- | ---------------------------- |
| 2022 French Open – men's singles (wd:Q107126329) | competition class (wdt:P2094) | men's singles (wd:Q16893072) |

[Assistant] I'll run a SPARQL query to find tennis events that are men's singles (P2094 -> Q16893072), are instances of tennis event (P31 -> Q46190676), have no winner (no P1346), and whose tournament (the item they are part of via P361) is part (possibly via multiple P361 steps) of either ATP Tour (Q300008) or Grand Prix tennis circuit (Q3775082). I'll execute the query next.

[Tool]
Got 24 rows and 4 columns, showing the first 5 and last 5 rows below:
| event                                                | eventLabel                                | tournament                                               | tournamentLabel                                 |
| ---------------------------------------------------- | ----------------------------------------- | -------------------------------------------------------- | ----------------------------------------------- |
| wd:Q99237069                                         |                                           | 2020 Italian Open – Men (wd:Q99312017)                   | 2020 Italian Open – Men (en)                    |
| wd:Q8354409                                          |                                           | wd:Q3875201                                              |                                                 |
| 1996 Salem Open Beijing – singles (wd:Q3674888)      | 1996 Salem Open Beijing – singles (en)    | 1996 Salem Open Beijing and the Nokia Open (wd:Q3674884) | 1996 Salem Open Beijing and the Nokia Open (en) |
| 2003 Open SEAT Godó – singles (wd:Q3994371)          | 2003 Open SEAT Godó – singles (en)        | 2003 Open SEAT Godó (wd:Q3994368)                        | 2003 Open SEAT Godó (en)                        |
| wd:Q3883469                                          | 2005 Open d'Orléans – singles (en)        | wd:Q3883467                                              | 2005 Open d'Orléans (en)                        |
| ...                                                  | ...                                       | ...                                                      | ...                                             |
| wd:Q134481286                                        | 2025 Geneva Open – Singles (en)           | wd:Q134127232                                            | 2025 Geneva Open (en)                           |
| 2025 Open 13 Provence – Singles (wd:Q132173811)      | 2025 Open 13 Provence – Singles (en)      | 2025 Open 13 Provence (wd:Q131860197)                    | 2025 Open 13 Provence (en)                      |
| 2025 Qatar ExxonMobil Open – Singles (wd:Q132360522) | 2025 Qatar ExxonMobil Open – Singles (en) | 2025 Qatar ExxonMobil Open (wd:Q131933979)               | 2025 Qatar ExxonMobil Open (en)                 |
| 2025 Rio Open – Singles (wd:Q132360560)              | 2025 Rio Open – Singles (en)              | 2025 Rio Open (wd:Q125836535)                            | 2025 Rio Open (en)                              |
| wd:Q135285254                                        | 2025 Swedish Open – Men's singles (en)    | wd:Q135103201                                            | 2025 Swedish Open (men) (en)                    |

[Assistant] I'll re-run the SPARQL query that finds tennis events which are men's singles (competition class Q16893072), have no winner (no P1346), and whose tournament (via P361) is part (P361*) of either ATP Tour (Q300008) or Grand Prix tennis circuit (Q3775082). Then I'll report the returned event and tournament identifiers and their English labels when available.

[Tool]
Got 24 rows and 4 columns, showing the first 5 and last 5 rows below:
| event                                                | eventLabel                                | tournament                                               | tournamentLabel                                 |
| ---------------------------------------------------- | ----------------------------------------- | -------------------------------------------------------- | ----------------------------------------------- |
| wd:Q99237069                                         |                                           | 2020 Italian Open – Men (wd:Q99312017)                   | 2020 Italian Open – Men (en)                    |
| wd:Q8354409                                          |                                           | wd:Q3875201                                              |                                                 |
| 1996 Salem Open Beijing – singles (wd:Q3674888)      | 1996 Salem Open Beijing – singles (en)    | 1996 Salem Open Beijing and the Nokia Open (wd:Q3674884) | 1996 Salem Open Beijing and the Nokia Open (en) |
| 2003 Open SEAT Godó – singles (wd:Q3994371)          | 2003 Open SEAT Godó – singles (en)        | 2003 Open SEAT Godó (wd:Q3994368)                        | 2003 Open SEAT Godó (en)                        |
| wd:Q3883469                                          | 2005 Open d'Orléans – singles (en)        | wd:Q3883467                                              | 2005 Open d'Orléans (en)                        |
| ...                                                  | ...                                       | ...                                                      | ...                                             |
| wd:Q134481286                                        | 2025 Geneva Open – Singles (en)           | wd:Q134127232                                            | 2025 Geneva Open (en)                           |
| 2025 Open 13 Provence – Singles (wd:Q132173811)      | 2025 Open 13 Provence – Singles (en)      | 2025 Open 13 Provence (wd:Q131860197)                    | 2025 Open 13 Provence (en)                      |
| 2025 Qatar ExxonMobil Open – Singles (wd:Q132360522) | 2025 Qatar ExxonMobil Open – Singles (en) | 2025 Qatar ExxonMobil Open (wd:Q131933979)               | 2025 Qatar ExxonMobil Open (en)                 |
| 2025 Rio Open – Singles (wd:Q132360560)              | 2025 Rio Open – Singles (en)              | 2025 Rio Open (wd:Q125836535)                            | 2025 Rio Open (en)                              |
| wd:Q135285254                                        | 2025 Swedish Open – Men's singles (en)    | wd:Q135103201                                            | 2025 Swedish Open (men) (en)                    |

[Assistant] The query returned 24 events. I must ensure the query returns the event and tournament IRIs (it does), and that it's correct. Now I'll finalize by returning the SPARQL query and summarizing the results: list the event IRIs and labels and their tournaments. As required, I must explain my thought process before and after each step and function call — I've been doing that. Now I'll call the answer function with the final SPARQL query and the answer.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?institution ( COUNT( DISTINCT ?thesis ) AS ?thesisCount ) ?institutionLabel WHERE {
  ?thesis wdt:P4101 ?institution .
  OPTIONAL {
    ?institution rdfs:label ?institutionLabel FILTER ( LANG( ?institutionLabel ) = "en" )
  }
}
GROUP BY ?institution ?institutionLabel
ORDER BY DESC ( ?thesisCount )
LIMIT 200

Got 200 rows and 3 columns, showing the first 5 and last 5 rows below:
| institution                                                                         | thesisCount     | institutionLabel                                                         |
| ----------------------------------------------------------------------------------- | --------------- | ------------------------------------------------------------------------ |
| University of Oxford (wd:Q34433)                                                    | 16831 (xsd:int) | University of Oxford (en)                                                |
| University of Auckland (wd:Q492467)                                                 | 14837 (xsd:int) | University of Auckland (en)                                              |
| Massey University (wd:Q1134606)                                                     | 11882 (xsd:int) | Massey University (en)                                                   |
| University of Canterbury (wd:Q432475)                                               | 11294 (xsd:int) | University of Canterbury (en)                                            |
| Delft University of Technology (wd:Q752663)                                         | 10779 (xsd:int) | Delft University of Technology (en)                                      |
| ...                                                                                | ...             | ...                                                                      |
| Fluminense Federal University (wd:Q280247)                                          | 14 (xsd:int)    | Fluminense Federal University (en)                                       |
| California State University, Long Beach (wd:Q1026926)                               | 13 (xsd:int)    | California State University, Long Beach (en)                             |
| University of New Mexico (wd:Q1190812)                                              | 13 (xsd:int)    | University of New Mexico (en)                                            |
| Australian National University (wd:Q127990)                                         | 13 (xsd:int)    | Australian National University (en)                                      |
| Illinois State University Depart...hy, Geology, and the Environment (wd:Q109321038) | 13 (xsd:int)    | Illinois State University Depart...hy, Geology, and the Environment (en) |

Top institutions by number of distinct theses/dissertations submitted to them (based on property P4101 "thesis submitted to"):

1. wd:Q34433 — University of Oxford — 16831
2. wd:Q492467 — University of Auckland — 14837
3. wd:Q1134606 — Massey University — 11882
4. wd:Q432475 — University of Canterbury — 11294
5. wd:Q752663 — Delft University of Technology — 10779
... (results limited; full query returns up to 200 institutions ordered by descending count)

Which institutions have the highest number of theses or dissertations submitted to them, ordered by the count of distinct theses or dissertations in descending order?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which institutions have the highest number of theses or dissertations submitted to them, ordered by the count of distinct theses or dissertations in descending order?

[Assistant] Step 1: I'll search for the Wikidata items for "thesis" and "dissertation" to identify the classes (instance of) used for theses. I'll also search for properties that link a thesis to an institution (likely "submitted to" or "academic advisor" etc.). I'll start by searching for entities "thesis" and "dissertation".

[Tool]
Top 10 entity alternatives:
1. thesis, also known as dissertation, theses, academic thesis, academic dissertation (wd:Q1266946)
2. Tesis, also known as Thesis (wd:Q1636502): 1996 film directed by Alejandro Amenábar, instance of film
3. Thesis (wd:Q3822612): instance of Greek primordial deity, goddess of Greek mythology
4. Thesis (wd:Q2420274)
5. thesis, also known as article, dissertation, paper, treatise (wd:Q124212544)
6. thesis (wd:Q4453731)
7. Thesis (wd:Q7783439): album by Jimmy Giuffre, instance of album
8. Thesis, also known as thesisband, Thesis band, Thesis (zespół rocka progresywnego) (wd:Q9358417): instance of rock band, Polish rock band
9. thesis (wd:Q123397500): for BFA, MFA or similar, instance of art genre
10. thesis (wd:Q20194793): weaker part of a musical feature, instance of musical concept

[Tool]
Top 10 property alternatives:
1. thesis submitted to, also known as dissertation submitted to, submitted to (wd:P4101 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): institution to whom a thesis or dissertation is submitted
2. applies to part, also known as applies to aspect, applied to, when viewed as, valid for part, section (wd:P518 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): part, aspect, or form of the item to which the claim applies
3. addressee, also known as to:, To:, addressed to, sent to, recipient (wd:P1817 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): person or organization to whom a letter or note is addressed, subproperty of destination of transfer
4. subject lexeme form, also known as form demonstrated, subject form, demonstrates form, applies to form (wd:P5830 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): (qualifier) statement applies only to listed lexeme forms of statement's subject
5. announcement date, also known as date teased, made public on, public announcement date, published, released (wd:P6949 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): time of the first public presentation of a subject by the creator, of information by the media, subproperty of point in time
6. publication date, also known as published, publication time, publication, pubdate, launched (wd:P577 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date or point in time when a work was first published or released, subproperty of point in time
7. number of submissions (wd:P12655 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): number of submissions, e.g., submitted papers to a conference
8. inception, also known as inception date, founding date, founded in, founded on date, founded on (wd:P571 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): time when an entity begins to exist; for date of official opening use P1619, subproperty of start time
9. contributed to creative work, also known as collaborator on, contributed to, contributed to work, contributor, contributor to (wd:P3919 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): person is cited as contributing to some creative or published work or series (qualify with "subject has role", P2868)
10. destination of transfer, also known as destination, to, target, recipient, receiver (wd:P12694 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): entity that a transferred item comes to be associated with as a result of this process

[Assistant] I'll inspect the item wd:Q1266946 ("thesis") to confirm it's the correct class for theses/dissertations and to see relevant properties like instance of. I'll list triples for that subject.

[Tool]
Got 489 rows and 3 columns, showing the first 10 rows below:
| subject              | property                         | object                                      |
| -------------------- | -------------------------------- | ------------------------------------------- |
| thesis (wd:Q1266946) | instance of (wdt:P31)            | literary genre (wd:Q223393)                 |
| thesis (wd:Q1266946) | Commons category (wdt:P373)      | Academic theses and dissertations           |
| thesis (wd:Q1266946) | subclass of (wdt:P279)           | research (wd:Q42240)                        |
| thesis (wd:Q1266946) | follows (wdt:P155)               | wd:Q134071597                               |
| thesis (wd:Q1266946) | different from (wdt:P1889)       | doctoral thesis (wd:Q187685)                |
| thesis (wd:Q1266946) | topic's main category (wdt:P910) | wd:Q15206881                                |
| thesis (wd:Q1266946) | exact match (wdt:P2888)          | <http://purl.org/coar/resource_type/c_46ec> |
| thesis (wd:Q1266946) | facet of (wdt:P1269)             | higher education (wd:Q136822)               |
| thesis (wd:Q1266946) | Wikidata property (wdt:P1687)    | academic thesis (wd:P1026)                  |
| thesis (wd:Q1266946) | equivalent class (wdt:P1709)     | <http://bibliograph.net/Thesis>             |
| ...                  | ...                              | ...                                         |

[Assistant] We found the property wd:P4101 "thesis submitted to". Now I will search for usage of P4101 to link theses to institutions. I'll search for triples where property is wdt:P4101 and list some examples.

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                                                             | property                        | object                                            |
| ----------------------------------------------------------------------------------- | ------------------------------- | ------------------------------------------------- |
| Exploring the Kingdom of Brychei...h in an Early Medieval Landscape (wd:Q100272640) | thesis submitted to (wdt:P4101) | University of Oxford (wd:Q34433)                  |
| The Early-Middle Bronze Age Tran...ex, Sussex and the Thames Valley (wd:Q104127077) | thesis submitted to (wdt:P4101) | University of Cambridge (wd:Q35794)               |
| Magnetism and Electron Transport...tive Lanthanum Calcium Manganite (wd:Q104889226) | thesis submitted to (wdt:P4101) | Stanford University (wd:Q41506)                   |
| Magnetic fields in the early solar system (wd:Q104536323)                           | thesis submitted to (wdt:P4101) | Massachusetts Institute of Technology (wd:Q49108) |
| The Riemann theory of trigonometric series (wd:Q100552965)                          | thesis submitted to (wdt:P4101) | Moscow State University (wd:Q13164)               |
| Coleção de bustos-relicários da ... de 30 esculturas do Século XVII (wd:Q105423991) | thesis submitted to (wdt:P4101) | Federal University of Minas Gerais (wd:Q132140)   |
| Entre tinteiros e palanques: A t... Feira de Santana-BA (1909-1930) (wd:Q107198442) | thesis submitted to (wdt:P4101) | State University of Feira de Santana (wd:Q156406) |
| Carybé e a legitimação de um dis...integração das artes em Salvador (wd:Q105303955) | thesis submitted to (wdt:P4101) | Federal University of Bahia (wd:Q159102)          |
| The smoothing of data (wd:Q104144515)                                               | thesis submitted to (wdt:P4101) | University of Edinburgh (wd:Q160302)              |
| The Polynomial Solutions of the ...quation A f(x+1) + B f(x) = Φ(x) (wd:Q104175639) | thesis submitted to (wdt:P4101) | Cornell University (wd:Q49115)                    |
| ...                                                                                | ...                             | ...                                               |

[Assistant] Now I'll run a SPARQL query that counts distinct items with property P4101 ("thesis submitted to") per institution, returning institution IRIs, English labels (when available), and the counts, ordered descending. I include a LIMIT 200 to keep the result manageable. Then I'll show the top results.

[Tool]
Got 200 rows and 3 columns, showing the first 5 and last 5 rows below:
| institution                                                                         | thesisCount     | institutionLabel                                                         |
| ----------------------------------------------------------------------------------- | --------------- | ------------------------------------------------------------------------ |
| University of Oxford (wd:Q34433)                                                    | 16831 (xsd:int) | University of Oxford (en)                                                |
| University of Auckland (wd:Q492467)                                                 | 14837 (xsd:int) | University of Auckland (en)                                              |
| Massey University (wd:Q1134606)                                                     | 11882 (xsd:int) | Massey University (en)                                                   |
| University of Canterbury (wd:Q432475)                                               | 11294 (xsd:int) | University of Canterbury (en)                                            |
| Delft University of Technology (wd:Q752663)                                         | 10779 (xsd:int) | Delft University of Technology (en)                                      |
| ...                                                                                | ...             | ...                                                                      |
| Fluminense Federal University (wd:Q280247)                                          | 14 (xsd:int)    | Fluminense Federal University (en)                                       |
| California State University, Long Beach (wd:Q1026926)                               | 13 (xsd:int)    | California State University, Long Beach (en)                             |
| University of New Mexico (wd:Q1190812)                                              | 13 (xsd:int)    | University of New Mexico (en)                                            |
| Australian National University (wd:Q127990)                                         | 13 (xsd:int)    | Australian National University (en)                                      |
| Illinois State University Depart...hy, Geology, and the Environment (wd:Q109321038) | 13 (xsd:int)    | Illinois State University Depart...hy, Geology, and the Environment (en) |

[Assistant] I'll run a refined SPARQL query to get the top 50 institutions by count of distinct theses submitted (using property P4101), returning institution IRIs, English labels, and the counts. This verifies and retrieves the top institutions for reporting.

[Tool]
Got 50 rows and 3 columns, showing the first 5 and last 5 rows below:
| institution                                                                    | thesisCount     | institutionLabel                                                    |
| ------------------------------------------------------------------------------ | --------------- | ------------------------------------------------------------------- |
| University of Oxford (wd:Q34433)                                               | 16831 (xsd:int) | University of Oxford (en)                                           |
| University of Auckland (wd:Q492467)                                            | 14837 (xsd:int) | University of Auckland (en)                                         |
| Massey University (wd:Q1134606)                                                | 11882 (xsd:int) | Massey University (en)                                              |
| University of Canterbury (wd:Q432475)                                          | 11294 (xsd:int) | University of Canterbury (en)                                       |
| Delft University of Technology (wd:Q752663)                                    | 10779 (xsd:int) | Delft University of Technology (en)                                 |
| ...                                                                            | ...             | ...                                                                 |
| Illinois State University School of Biological Sciences (wd:Q109321032)        | 92 (xsd:int)    | Illinois State University School of Biological Sciences (en)        |
| Illinois State University School of Kinesiology and Recreation (wd:Q109320549) | 90 (xsd:int)    | Illinois State University School of Kinesiology and Recreation (en) |
| Illinois State University School of Communication (wd:Q109321034)              | 84 (xsd:int)    | Illinois State University School of Communication (en)              |
| University of Paris (wd:Q209842)                                               | 83 (xsd:int)    | University of Paris (en)                                            |
| University of Göttingen (wd:Q152838)                                           | 73 (xsd:int)    | University of Göttingen (en)                                        |

[Assistant] The query returns reasonable results. Now per the instructions, I must explain my thought process before and after each step and function call (I have been doing that). I also must ensure the final SPARQL query returns identifiers/IRIs. My final answer should include the SPARQL query and the answer. I'll prepare the final SPARQL query (which we executed) and provide the top institutions and counts as the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?year ( COUNT( DISTINCT ?ensemble ) AS ?count ) WHERE {
  ?ensemble wdt:P31 / wdt:P279 * wd:Q2088357 .
  ?ensemble wdt:P571 ?inception .
  BIND( YEAR( ?inception ) AS ?year ) FILTER ( BOUND( ?year ) ) FILTER ( ?year >= 1000 && ?year <= 2025 )
}
GROUP BY ?year
ORDER BY ?year

I counted items that are instances (or instances of subclasses) of 'musical ensemble' (wd:Q2088357) and have an inception date (wdt:P571). The query groups them by the YEAR of inception and sorts by year. Results show the number of musical ensembles formed each year between 1000 and 2025 (inclusive). The query returns rows like (year, count). Example recent counts from the query: 2021: 156, 2022: 152, 2023: 99, 2024: 55, 2025: 29. The full result set contains 294 years with counts.

How many musical ensembles were formed each year, grouped by the year of their inception and sorted by year?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many musical ensembles were formed each year, grouped by the year of their inception and sorted by year?

[Assistant] Step 1: I'll search for the Wikidata item for "musical ensemble" and confirm the property used for inception (likely P571). I'll also look for common subclass items (e.g., band, orchestra) if needed. I'll run searches to verify identifiers.

[Tool]
Top 10 entity alternatives:
1. musical ensemble, also known as music ensemble, ensemble (wd:Q2088357)
2. vocal-musical ensemble, also known as musical ensemble (wd:Q29881657)
3. musical ensemble (wd:L34511-S1)
4. Kantele (musical ensemble), also known as Kantele (wd:Q4212623): instance of musical ensemble
5. instrumental ensemble, also known as instrumental musical ensemble (wd:Q11072804)
6. fictional musical ensemble, also known as fictional band, fictional music group, fictional music ensemble, fictional music band, fictional musical group (wd:Q6619719)
7. composition for concertina ensemble, also known as concertina ensemble (musical work), concertina ensemble (wd:Q108040793)
8. Fondateur d'un ensemble musical (wd:Q105103965): instance of human
9. Musical Ensemble Erft e.V. (wd:Q122855895): amateur theater in North Rhine-Westphalia (Germany), instance of theatre troupe
10. member of this band, musical group, also known as member of this musical ensemble, member of this musical group, member of this band, band members by band (wd:Q65966973)

[Assistant] I'll verify that 'inception' is used as the property for the founding/inception date in Wikidata (P571). Then I'll check usage for musical ensembles to ensure items have P571.

[Tool]
Top 10 property alternatives:
1. inception, also known as inception date, founding date, founded in, founded on date, founded on (wd:P571 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): time when an entity begins to exist; for date of official opening use P1619, subproperty of start time
2. introduced on, also known as bill introduced on, introduction date, introduced date (wd:P9448 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date when a bill was introduced into a legislature, subproperty of inception
3. date of promulgation, also known as assent, date of approval, date of assent, date signed, enacted date (wd:P7589 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date on which a piece of legislation formally became law (whether by assent or some other procedure), subproperty of point in time
4. date depicted, also known as date shown, depicted date, depicted time, depicts date, shown as at date (wd:P2913 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date represented in a work (for narrative works use P2408)
5. latest date, also known as terminus ante quem, prior to, on or before this date, no later than, maximum date (wd:P1326 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): latest possible time that something could have occurred. Use as qualifier for other date properties
6. announcement date, also known as date teased, made public on, public announcement date, published, released (wd:P6949 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): time of the first public presentation of a subject by the creator, of information by the media, subproperty of point in time
7. effective date, also known as enforcement date, date of commencement, date of coming into force (wd:P7588 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date on which a statutory or administrative law or other officia...This may also be retrospective, predating the date of enactment., subproperty of point in time
8. date of incorporation, also known as date incorporated, incorporated, incorporated on date, incorporation date, year incorporated (wd:P10786 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date when company, organization or city was incorporated
9. UTC date of spacecraft landing, also known as date of spacecraft landing, time of spacecraft landing, spacecraft landing time, landing time, landing date (wd:P620 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): date of spacecraft landing in UTC
10. start time, also known as start date, since, join time, joined, join date (wd:P580 as pqv/ps/psv/pq/prv/wdt/p/prn/psn/pqn/wdtn/pr): time an entity begins to exist or a statement starts being valid, subproperty of point in time

[Assistant] I'll test a simple query: find musical ensembles (instances of wd:Q2088357) that have inception (wdt:P571) and retrieve their inception year. I'll run a SPARQL SELECT to get some sample results.

[Tool]
Got 20 rows and 3 columns, showing the first 5 and last 5 rows below:
| ensemble                                                              | ensembleLabel                                              | inception                           |
| --------------------------------------------------------------------- | ---------------------------------------------------------- | ----------------------------------- |
| Israel Chamber Ensemble (wd:Q101068199)                               | Israel Chamber Ensemble (en)                               | 1965-01-01T00:00:00Z (xsd:dateTime) |
| Société de musique de chambre pour instruments à vent (wd:Q101529041) | Société de musique de chambre pour instruments à vent (en) | 1879-01-01T00:00:00Z (xsd:dateTime) |
| Société moderne d'instruments à vent (wd:Q101780297)                  | Société moderne d'instruments à vent (en)                  | 1895-01-01T00:00:00Z (xsd:dateTime) |
| Cosmopolitan Music Society (wd:Q102046864)                            | Cosmopolitan Music Society (en)                            | 1963-01-01T00:00:00Z (xsd:dateTime) |
| Detentos do Rap (wd:Q10265739)                                        | Detentos do Rap (en)                                       | 1998-01-01T00:00:00Z (xsd:dateTime) |
| ...                                                                   | ...                                                        | ...                                 |
| Le Concert de la Loge (wd:Q106813223)                                 | Le Concert de la Loge (en)                                 | 2015-01-01T00:00:00Z (xsd:dateTime) |
| Margasatwa (wd:Q107359443)                                            | Margasatwa (en)                                            | 2016-01-01T00:00:00Z (xsd:dateTime) |
| Blue Streak Ensemble (wd:Q107433630)                                  | Blue Streak Ensemble (en)                                  | 2011-01-01T00:00:00Z (xsd:dateTime) |
| TwoVm Para Cristo (wd:Q107503121)                                     | TwoVm Para Cristo (en)                                     | 2009-01-01T00:00:00Z (xsd:dateTime) |
| Neoteric Chamber Winds (wd:Q107578947)                                | Neoteric Chamber Winds (en)                                | 2011-01-01T00:00:00Z (xsd:dateTime) |

[Assistant] I'll run a SPARQL query that groups items that are instances of (or instances of subclasses of) "musical ensemble" (wd:Q2088357) by the YEAR of their inception (wdt:P571), counting distinct ensembles per year and sorting by year. This includes ensembles whose instance-of class is a subclass of musical ensemble. Now I'll execute the query.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The expression "YEAR ( ?inception )" does not aggregate ?inception. All non-aggregated variables must be part of the GROUP BY clause.

[Assistant] The previous query failed because YEAR(?inception) wasn't included in the GROUP BY. I'll run a corrected query that groups by the expression YEAR(?inception).

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The expression "YEAR ( ?inception )" does not aggregate ?inception. All non-aggregated variables must be part of the GROUP BY clause.

[Assistant] I'll run a corrected query that binds the year from the inception date and groups by that year. Then I'll execute it to get counts per year.

[Tool]
Got 302 rows and 2 columns, showing the first 5 and last 5 rows below:
| year             | count         |
| ---------------- | ------------- |
|                  | 24 (xsd:int)  |
| 1 (xsd:int)      | 1 (xsd:int)   |
| 19 (xsd:int)     | 1 (xsd:int)   |
| 198 (xsd:int)    | 1 (xsd:int)   |
| 785 (xsd:int)    | 1 (xsd:int)   |
| ...              | ...           |
| 2022 (xsd:int)   | 152 (xsd:int) |
| 2023 (xsd:int)   | 99 (xsd:int)  |
| 2024 (xsd:int)   | 55 (xsd:int)  |
| 2025 (xsd:int)   | 29 (xsd:int)  |
| 806868 (xsd:int) | 1 (xsd:int)   |

[Assistant] Now I'll refine the query to exclude invalid years and restrict results to a reasonable year range (1000–2025) to avoid malformed dates, then execute it to get the final counts per year.

[Tool]
Got 294 rows and 2 columns, showing the first 5 and last 5 rows below:
| year           | count         |
| -------------- | ------------- |
| 1127 (xsd:int) | 1 (xsd:int)   |
| 1200 (xsd:int) | 1 (xsd:int)   |
| 1201 (xsd:int) | 2 (xsd:int)   |
| 1210 (xsd:int) | 1 (xsd:int)   |
| 1213 (xsd:int) | 1 (xsd:int)   |
| ...            | ...           |
| 2021 (xsd:int) | 156 (xsd:int) |
| 2022 (xsd:int) | 152 (xsd:int) |
| 2023 (xsd:int) | 99 (xsd:int)  |
| 2024 (xsd:int) | 55 (xsd:int)  |
| 2025 (xsd:int) | 29 (xsd:int)  |

[Assistant] The query looks good. I'll prepare the final answer with the SPARQL query and explain the approach and results. Now I'll call the answer function to return the final SPARQL query and the summary of results.

[Tool] Stopped generation process